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Collaborative Optimization Using Response Surface Estimation

2000; American Institute of Aeronautics and Astronautics; Volume: 38; Issue: 10 Linguagem: Inglês

10.2514/2.847

1533-385X

I. P. Sobieski, Ilan M. Kroo,

Probabilistic and Robust Engineering Design

The use of response surface estimation in collaborative optimization, an architecture for large-scale multidisciplinary design is described. Collaborative optimization preserves the autonomy of individual disciplines while providing a mechanism for coordinating the overall design problem and progressing toward improved designs. Collaborative optimization is a two-level optimization architecture, with discipline-specific optimizations free to specify local designs, and a global optimization that ensures that all of the discipline designs eventually agree on a single value for those variables that are shared in common. Results demonstrate how response surface models of subproblem optimization results improve the performance of collaborative optimization. The utility of response surface estimation in collaborative optimization depends on the generation of inexpensive accurate response surface models and the refinement of these models over several fitting cycles. Special properties of the subproblem optimization formulation are exploited to reduce the number of required subproblem optimizations to develop a quadratic model from O(n 2 ) to O(n/2). Response surface refinement is performed using ideas from trust region methods. Results for the combined approaches are compared through the design optimization of a tailless unmanned air vehicle in 44 design variables.